Dataset Information

Serum protein signature of coronary artery disease in type 2 diabetes mellitus.

ABSTRACT:

Background

Coronary artery disease (CAD) is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). The purpose of the present study was to discriminate the Indian CAD patients with or without T2DM by using multiple pathophysiological biomarkers.

Methods

Using sensitive multiplex protein assays, we assessed 46 protein markers including cytokines/chemokines, metabolic hormones, adipokines and apolipoproteins for evaluating different pathophysiological conditions of control, T2DM, CAD and T2DM with CAD patients (T2DM_CAD). Network analysis was performed to create protein-protein interaction networks by using significantly (p?ResultsOur two supervised analysis methods BCA and PCA revealed a distinct biomarker profiles and high degree of variability in the marker profiles for T2DM_CAD and CAD. Thereafter, the present study identified multiple potential biomarkers to differentiate T2DM, CAD, and T2DM_CAD patients based on their relative abundance in serum. RF classified T2DM based on the abundance patterns of nine markers i.e., IL-1?, GM-CSF, glucagon, PAI-I, rantes, IP-10, resistin, GIP and Apo-B; CAD by 14 markers i.e., resistin, PDGF-BB, PAI-1, lipocalin-2, leptin, IL-13, eotaxin, GM-CSF, Apo-E, ghrelin, adipsin, GIP, Apo-CII and IP-10; and T2DM _CAD by 12 markers i.e., insulin, resistin, PAI-1, adiponectin, lipocalin-2, GM-CSF, adipsin, leptin, Apo-AII, rantes, IL-6 and ghrelin with respect to the control subjects. Using network analysis, we have identified several cellular network proteins like PTPN1, AKT1, INSR, LEPR, IRS1, IRS2, IL1R2, IL6R, PCSK9 and MYD88, which are responsible for regulating inflammation, insulin resistance, and atherosclerosis.

Conclusion

We have identified three distinct sets of serum markers for diabetes, CAD and diabetes associated with CAD in Indian patients using nonparametric-based machine learning approach. These multiple marker classifiers may be useful for monitoring progression from a healthy person to T2DM and T2DM to T2DM_CAD. However, these findings need to be further confirmed in the future studies with large number of samples.

SUBMITTER: Adela R

PROVIDER: S-EPMC6345069 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Serum protein signature of coronary artery disease in type 2 diabetes mellitus.

Adela Ramu R Reddy Podduturu Naveen Chander PNC Ghosh Tarini Shankar TS Aggarwal Suruchi S Yadav Amit Kumar AK Das Bhabatosh B Banerjee Sanjay K SK Banerjee Sanjay K SK

Journal of translational medicine 20190124 1

<h4>Background</h4>Coronary artery disease (CAD) is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). The purpose of the present study was to discriminate the Indian CAD patients with or without T2DM by using multiple pathophysiological biomarkers.<h4>Methods</h4>Using sensitive multiplex protein assays, we assessed 46 protein markers including cytokines/chemokines, metabolic hormones, adipokines and apolipoproteins for evaluating different pathophysi ...[more]

PMID: 30674322

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Project description:BackgroundNeutrophil extracellular traps NETs have been linked to glucose and the pathogenesis of type 1 diabetes mellitus (T1DM). NETs also play a role in vascular inflammation and the development of coronary artery disease (CAD). The role of NETs in CAD progression in patients with long-term T1DM is unclear. We aimed to 1) investigate whether levels of circulating NETs markers were elevated in long-term T1DM subjects compared to controls, and 2) explore whether levels of NETs were related to the presence of CAD.Material and methods102 patients with > 45 years of T1DM and 75 age-matched controls were enrolled in a cross-sectional study. Median age was 62 years. Computed tomography coronary angiography (CTCA) was performed in 148 subjects without established coronary heart disease. For the current study, CAD was defined as a coronary artery stenosis >50%. Double-stranded deoxyribonucleic acid (dsDNA) was measured by a nucleic acid stain, myeloperoxidase-DNA (MPO-DNA), citrullinated histone 3 (H3Cit) and peptidylarginine deiminase 4 (PAD4) by ELISAs, while gene expression of PAD4 was measured in leukocytes from PAXgene tubes.ResultsCirculating MPO-DNA levels were significantly lower in patients with T1DM than in controls (0.17 vs 0.29 OD, p<0.001), while dsDNA, H3Cit, PAD4 and gene expression of PAD4 did not differ with respect to the presence of T1DM. There were no significant associations between NETs markers and HbA1c in the T1DM group. None of the NETs markers differed according to the presence of CAD in patients with T1DM. While all circulating NETs markers correlated significantly with circulating neutrophils in the control group (r=0.292-393, p<0.014), only H3Cit and PAD4 correlated with neutrophils in the T1DM group (r= 0.330-0.449, p ≤ 0.001).ConclusionsIn this cross-sectional study of patients with long-term T1DM and age-matched controls, circulating NETs levels were not consistently associated with the presence of T1DM or glycemic status, and did not differ according to the presence of CAD in patients with T1DM. Our results entail the possibility of altered neutrophil function and reduced NETosis in T1DM. This warrants further investigation.

Dataset Information

Serum protein signature of coronary artery disease in type 2 diabetes mellitus.

Background

Methods

Conclusion

Publications

Serum protein signature of coronary artery disease in type 2 diabetes mellitus.

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